Open-source code development has become widespread in recent years. As a result, open-source software platforms have also become popular, and millions of developers from diverse locations are able to contribute to the same projects. On these platforms, various knowledge about them is obtained from user activity. This information is used in the form of developer metrics to solve a variety of challenges. In this study, we proposed new developer metrics, including commenting and issue-related activity, that require less information. We concluded that commenting on any feature of a project can be equally as valuable as code contribution. In addition, besides the quantitative ones, metrics based on only the existence of the activity have been shown to offer also considerable results. We saw that issues were crucial in identifying user contributions. Even if a developer makes a contribution to only one issue on a project, the relation between the developer and the project is tight. The hit scores are relatively lower because of the sparsity problem of our dataset; even so, we believe that we have presented improvable and remarkable new developer metrics.

中文翻译：

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新的开发人员指标：评论与代码贡献一样重要吗？

近年来，开源代码开发已变得普遍。因此，开源软件平台也变得流行起来，来自不同地区的数百万开发人员能够为相同的项目做出贡献。在这些平台上，有关它们的各种知识是从用户活动中获得的。此信息以开发人员指标的形式使用，以解决各种挑战。在这项研究中，我们提出了新的开发人员指标，包括需要较少信息的评论和与问题相关的活动。我们得出的结论是，对项目的任何功能进行评论与代码贡献同等重要。此外，除了定量指标外，仅基于活动存在的指标也已显示出可观的结果。我们看到问题对于识别用户贡献至关重要。即使开发人员只对项目的一个问题做出贡献，开发人员与项目之间的关系也很紧密。由于我们数据集的稀疏性问题，命中分数相对较低；即便如此，我们相信我们已经提出了可改进且卓越的新开发人员指标。